Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use hebashakeel/bert-wellness-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hebashakeel/bert-wellness-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hebashakeel/bert-wellness-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hebashakeel/bert-wellness-classifier") model = AutoModelForSequenceClassification.from_pretrained("hebashakeel/bert-wellness-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bef228a1c2598325fd23124a5220b2e78a15362df7c0ce2bc831f52e5a020bcd
- Size of remote file:
- 438 MB
- SHA256:
- e2496c18e769658eed43a2a49f8a79e547a723305e5722db6ef743267aa1337d
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